In inverse problems, we try to recover data from indirect measurements resulting from an ill-posed forward process. In the last few years, deep learning has shown great abilities to enhance such reconstruction techniques. Topics of interest include, learned regularisation schemes, statistical and optimisation approaches such as generative priors, plug-and-play methods, unrolled networks and neural operators for solving PDEs. Additionally, we are interested in uncertainty quantification for such reconstruction methods, for instance via Bayesian methods. Applications include problems from medical and non-medical image and signal processing, physics and engineering.
In this meeting, from 7-9 July 2025, in Bath, we aim to bring together experts from the fields of inverse problems and deep learning focusing on theoretical and practical questions.
Apart from the keynote talks, we will have an open call for contributed talks and posters starting in November 2024.
Please check back in November 2024 for more information.
Registration will open shortly. In the meantime, if you have any questions about the conference, please email maths4dl@bath.ac.uk.
